Non-Pharmacological Sleep Interventions for Dementia Caregivers;A Systematic Review of Randomized Controlled Trials

Abstract

Background

Caregivers of people living with dementia frequently report poor sleep. This systematic review describes evidence from randomised controlled trials of non-pharmacological sleep interventions for dementia carers.

Methods

A systematic search of major databases was undertaken. Risk of bias was assessed using the Cochrane ROB 2.0 tool. Narrative synthesis followed Synthesis Without Meta-analysis (SWiM) guidelines due to substantial heterogeneity.

Findings

Eighteen articles were included. Risk of Bias analyses revealed most studies had high overall risk of bias, primarily from selection of reported result bias. Interventions comprised of five categories: sleep-promoting, carer well-being, exercise, technology-based and complementary therapy. High variability between intervention type, duration, sample size and sleep measures impeding direct comparisons. Seven studies (39%) identified statistically significant improvements in caregivers sleep from exercise interventions, multi-component interventions and psychological support interventions.

Conclusions

Exercise and psychological support interventions demonstrated the most promising effects, though larger, high-quality trials are needed for definitive evidence.

Keywords

dementia caregivers sleep promotion sleep intervention non-pharmacological

What This Paper Adds

• First systematic review of RCT evidence for non-pharmacological sleep interventions for dementia caregivers, with exercise interventions demonstrated the most consistent benefits to carers sleep.

• Reveals a critical gap in high quality, adequately powered RCTs, thus limiting definitive conclusions.

Applications of Study Findings

• This review identified that caregiver sleep remains an under-researched area, despite poor caregiver sleep being associated with poorer caregiver outcomes and increased risk of institutionalisation for the person living with dementia. Scalable, effective sleep interventions have the potential to reduce downstream costs and health systems pressures, underscoring the urgency for further well-designed research.

• Multi-component sleep-promoting programs and exercise-based interventions should be considered as first-line non-pharmacological options, given they demonstrate the most consistent evidence of benefit in this review. Psychological and stress reduction interventions show promise, warranting further research. However, the majority of included studies were rated as high risk of bias, highlighting the need for well-designed, adequately powered RCTs to generate a robust evidence base.

Introduction

Sleep is a fundamental biological requirement which forms a cornerstone of optimal health and wellbeing. Poor sleep has been associated with a myriad of health complications including cardiovascular disease, obesity, diabetes, dementia and even increased mortality (Itani et al., 2017; Xu et al., 2020). Adults require seven to 9 hours of good quality sleep per night (House of Representatives Standing Committee on Health Aged Care and Sport, 2019), however, there remains disparity of sleep quality and quantity across different adult populations. Caregivers of a person living with dementia (PLWD) are some of the most chronically under slept populations. Poor carer sleep is due to a myriad of reasons including depression, anxiety, psychological burden, stress, overnight caring responsibilities or rumination (Elliott et al., 2010; Gao et al., 2019; Smyth et al., 2020). Studies show that 94% of dementia caregivers experienced poor quality sleep (Smyth et al., 2020), with weekly sleep deficits of 2.4 to 3.5 hours compared to non-caregivers (Australian Institute of Health and Welfare, 2012; Gao et al., 2019). These sleep disturbances significantly impact caregiver health and quality of life (Byun et al., 2016; Cupidi et al., 2012).

Worldwide, there is approximately 50 million people with dementia and almost 10 million new cases annually (World Health Organization, 2020), associated with 82 billion hours of informal care (Wimo et al., 2018). To facilitate the carer to continue to provide care and to protect their own health, we must identify and implement successful, evidence-based means of promoting carers sleep. However, there remains a dearth of evidence relating to dementia caregivers sleep and even less pertaining to successful sleep promoting interventions in this group (Jay et al., 2019). Whilst care-related awakenings may be unavoidable, it is essential to implement strategies which protect and optimise carers potential sleep quality and quantity.

Sleep management requires an individualised approach, as the underlying origins can be varied and complex. Treatment can be broadly defined as pharmacological or non-pharmacological. Whilst pharmacological treatment of poor sleep has its place, such as short term alleviation of insomnia and increase in sleep time (Schutte-Rodin et al., 2008), long-term sleeping medication usage is associated with adverse consequences such as residual sedation, cognitive and psychomotor impairments and anterograde amnesia, as well as tolerance to, and dependency on, the pharmaceutical agent (Vermeeren, 2004; Vermeeren et al., 2002). It is therefore essential to identify non-pharmaceutical interventions that improve sleep in caregivers.

Despite availability of various sleep interventions, the most effective non-pharmacological approaches for dementia carers remain unclear. As far as the authors are aware, RCTs of non-pharmacological sleep interventions for dementia carers have not yet been systematically reviewed. Given the high quality of RCT research design, a thorough understanding of what interventions improve the sleep quality and quantity of carers of PLWD can provide important high-quality evidence around successful strategies to mitigate poor sleep in dementia carers.

This review aims to systematically identify and evaluate randomised controlled trials on non-pharmacological sleep promoting interventions in caregivers of PLWD.

Methods

The systematic review followed the guidelines created by Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) (Moher et al., 2009; Page et al., 2021). The study protocol was registered with PROSPERO (Registration number: CRD420200211848).

Search Strategy and Selection Criteria

The search strategy targeted research studies from inception to May 2025. The databases searched included Cumulative Index for Nursing and Allied Health Literature (CINAHL), Medical Literature Analysis and Retrieval System Online (MEDLINE), ProQuest, PsycINFO, OVID and PubMed. The search was performed using a combination of search terms including dementia, care, caregiver, sleep, sleep quality, sleep hygiene, and intervention. Medical Subject Headings were searched where possible. The full search strategy can be viewed in Appendix 1.

Inclusion Criteria

The inclusion criteria for this systematic review were established using the PICO framework (Population, Intervention, Control, Outcome) (Pollock & Berge, 2018).

Population: Informal caregivers of a person living with dementia of any type, where both the caregiver and the care recipient were living in the community.

Intervention: Any non-pharmacological intervention aimed at dementia caregiver populations. Interventions included, but were not limited to, cognitive behavioural therapy, psychological support, carer-focused support, stress management, exercise, technology assistance, meditation, mindfulness, yoga, music and sleep hygiene. There were no restrictions on period or frequency of intervention. Sleep was not required to be the primary interventional outcome.

Control: Studies were required to include a comparator group, including but not limited to, usual care, waitlist control or alternative conditions.

Outcome: Studies were required to include at least one measure of caregiver sleep as an outcome. Sleep outcomes encompassed both subjective (including but not limited to validated questionnaires, sleep diaries, and self-report scales) and/or objective measures of carers sleep (including but not limited to actigraphy, polysomnography). Specific sleep parameters of interest include sleep quality, sleep duration, sleep latency, sleep efficiency, wake after sleep onset, total sleep time, number of wakening’s, sleep disturbances, daytime sleepiness, daytime dysfunction, and insomnia severity.

Study Design

All included articles were randomised controlled trials (RCTs). Studies were excluded if they were: conference abstracts; conference posters; protocols; if the study was a qualitative design; examined formal caregivers; examined patients with dementia living in residential aged care facilities; if the caregiver had a cognitive impairment; or; any intervention with a pharmacological component, including natural and/or herbal medications and melatonin. Studies which included dyadic interventions and clearly reported carer results separately were included.

Study Selection

Each article was reviewed by at least two reviewers (KL, SS) who both screened the titles and abstracts using Covidence. Full-text screening was performed independently with disagreements resolved through discussion or consultation with a third reviewer (AS) when consensus could not be reached. PRISMA reporting guidelines were followed throughout the review process (Page et al., 2021) (Figure 1).

Figure 1.

PRISMA 2020 flow diagram

Risk of Bias Assessment

The risk of bias for each study was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool (Sterne et al., 2019). This tool evaluates potential sources of bias across five domains: bias arising from the randomisation process, bias due to deviations from intended interventions, bias due to missing outcome data, bias in outcome measurement and bias in selection of the reported result. Each domain was rated as having a low risk of bias, some concerns or high risk of bias according to RoB2 criteria. Overall risk of bias judgements were determined using the ROB2 algorithm, whereby a study receiving a high risk rating in any single domain was typically classified as high overall risk of bias, unless the issue was judged unlikely to substantially affect the specific outcome being assessed (Sterne et al., 2019). Given that sleep outcomes were measured either subjectively (via self-report questionnaires) or objectively (via actigraphy), high-risk ratings in domains such as outcome measurement, missing outcome data, and selection of reported results were considered particularly likely to bias effect estimates. All assessments were conducted independently (KL, SS) with agreements resolved through consultation with the first author (AS).

Data Extraction

Pre-designed templates were utilised to extract data from the included studies. The following data were extracted: authors, year of publication, study setting, participant demographics including age, gender, and ethnicity; length of care; type of RCT design; intervention length; follow-up intervention length; comparator; sleep measure; carer sleep findings. If the data was not available in the full text article, we contacted the corresponding authors to obtain the missing data. Data extraction was completed and cross checked by two reviewers (AS, KL). The sample sizes (n) reported in this review refer exclusively to caregiver participants. Although some included studies recruited both caregivers and people with dementia, outcomes were analysed separately by participant type, and only caregiver-specific outcomes were extracted for this systematic review.

Synthesis of Results

Assessment of included studies revealed substantial heterogeneity across multiple dimensions including intervention types, outcome definitions, population characteristics, and methodological approaches, precluding meaningful statistical pooling (Higgins JPT, 2024). Therefore, narrative synthesis was conducted following the Synthesis Without Meta-analysis (SWiM) reporting guidelines (Campbell et al., 2020), grouping studies by intervention category and examining patterns of effects within and across intervention types.

Results

Characteristics of Included Studies

Description of Included Studies

A total of 18 RCTs containing interventions aimed at improving sleep were included in analyses (Table 1). Studies were conducted in China (Xu et al., 2022), Japan (Hirano et al., 2011), England (Kinnunen et al., 2018; Rapaport et al., 2024), Thailand (Sanprakhon et al., 2023) and the United States of America (Akkerman & Ostwald, 2004; Elliott et al., 2010; Fowler et al., 2016; Friedman et al., 2012; King et al., 2002; Korn et al., 2009; Oken et al., 2010; Rose et al., 2009; Rowe et al., 2010; Scheffer et al., 2025; Sloane et al., 2015; Song et al., 2024; Williams et al., 2019). Combining all RCTs, there was a total of 1,747 caregiver participants with a mean sample size of 96 participants, and an overall range of 15–495 participants across all included studies. Participants age ranged from 50 to 74.2 years (mean 68.2 ± 7.4 years). The mean length of care was 43.8 ± 14.7 months (n = 5), with the study population being 77.0% female on average. Summary characteristics of included studies can be seen in Table 1, with detailed study characteristics available in Appendix 2.

Table 1.

Summary of Included Studies: Interventions and Key Sleep Outcomes (n = 18)

Study (Country)	n	RCT Design	Intervention	Key Findings
Sleep promoting interventions
Friedman et al. (2012)^a (USA)	54	Parallel	Brief morning light therapy (bright white vs dim red) + sleep hygiene education; 2 weeks	Both groups improved in actigraphy measured WASO and sleep efficiency (p < 0.05), as well as subjective measures of insomnia, depression and daytime sleepiness; no differential effect between light conditions; improvements attributed to sleep hygiene component
Kinnunen et al. (2018) (England)	62	Parallel	DREAMS START (feasibility): 6-session manual-based multimodal program consisting of sleep education, light therapy, activity, dementia management; 3 months	No significant differences: PSQI intervention 9.37 ± 4.16 vs control 9.54 ± 4.49 (p > 0.05)
Rapaport et al. (2024)^a (England)	259	Parallel	DREAMS START (phase 3 RCT): 6-Session multicomponent sleep intervention including CBT-I, light, activity, support; 3 months	Significant improvement: SCI intervention 17.60 ± 8.60 vs control 15.73 ± 8.53; adjusted difference 1.84 (95% CI 0.32–3.35, p < 0.05); clinical insomnia to non-clinical levels
Sloane et al. (2015)^a (USA)	17	Crossover	Blue-white light therapy (vs red-yellow control); 6 weeks in-home	Significant improvements: PSQI global (p = 0.013), MOS sleep problems (p = 0.011), MOS sleep adequacy (p = 0.046); baseline PSQI 4.6 (already good sleep)
Song et al. (2024) (USA)	30	Parallel	Care2Sleep: 5-Session manual combining CBT-I, light exposure, walking, behavioural problem-solving	Non-significant improvements: 3.2% sleep efficiency increase (p = 0.39); 12-minute reduction in wake time (p = 0.2)
Exercise interventions
Hirano et al. (2011) ^a (Japan)	31	Parallel	Moderate intensity exercise 3×/week; 12 weeks	Exercise group: Significant sleep improvement (−0.5, p = 0.04); control: Significant worsening (+0.7, p = 0.01); baseline sleep differences between groups noted
King et al. (2002)^a (USA)	100	Parallel	12-month moderate intensity endurance exercise program	Significant protection against declining sleep quality: F (6,74) = 2.9, p = 0.045; correlated with reduced stress (r = 0.33) and carer burden (r = 0.33)
Complementary therapies
Korn et al. (2009) (USA)	42	Parallel	Polarity therapy: 8 × 50-minute sessions of complementary energy therapy	Non-significant 3.1 ± 3.88 point reduction in PSQI (may indicate clinical improvement but not statistically significant)
Rose et al. (2009) (USA)	38	Parallel	Cranial electrical stimulation (CES): Daily 60-minute sessions; 4 weeks	No significant differences between groups on PSQI or GSDS measures
Technology-based support
Fowler et al. (2016) (USA)	28	Parallel	Virtual healthcare neighbourhood: Online peer support, education, MDT access; 4 months	No significant improvements; ISI minimal change 15.3→14.3 (not significant), however control group insomnia scores worsened during trial period suggesting potential protective benefits.
Rowe et al. (2010) (USA)	49	Parallel	Nighttime monitoring system: Sensors alerting caregivers to all nighttime activity	No significant differences in PSQI or actigraphy; both groups showed high unwanted wake time
Scheffer et al. (2025) (USA)	162	Crossover	People power caregiver system: AI-powered smart home monitoring with selective alerts; 9 months	Initial significance for sleep efficiency in treatment group (p = 0.038, Cohen’s d = −0.76) but did NOT survive FDR correction for multiple comparisons
Williams et al. (2019) (USA)	83	Parallel	FamTechCare: Video monitoring with individualised feedback and support; 3 months	No significant differences in sleep disturbance between groups (p = 0.839)
Psychological support
Akkerman and Ostwald (2004) (USA)	38	Crossover	9-week group CBT intervention	Preliminary positive effects (90-minute reduction in overnight wake); actigraphy sample too small (n = 5) for statistical analysis
Elliott et al. (2010) (USA)	495	Parallel	REACH II: multicomponent intervention including individualised risk profiles; 9 in-home +3 telephone sessions; 6 months	Pattern of improvement in intervention group (not statistically significant)
Oken et al. (2010) (USA)	31	Multiarmed	Mindfulness meditation (vs education control); 6 sessions	No significant differences in PSQI or ESS scores
Sanprakhon et al. (2023)^a (Thailand)	54	Parallel	Integrative stress reduction program; 4 weeks	Significant improvement: Intervention 11.74→5.63, control 9.33→7.93; F (1,51) = 24.45, p < 0.01, partial η² = 0.324; clinically meaningful 6.1-point reduction; baseline group differences noted in sleep measures
Xu et al. (2022)^a (China)	71	Parallel	8-week telephone-based behavioural activation intervention	Significant effects: C-PSQI global F (1,69) = 6.32, p = 0.014; sleep efficiency F (1,69) = 5.50, p = 0.022; baseline group differences noted in sleep measures

n = number of caregiver participants. CBT-I = Cognitive Behavioural Therapy for Insomnia; C-PSQI = Chinese Pittsburgh Sleep Quality Index; CES = Cranial Electrical Stimulation; FDR = False Discovery Rate; GSDS = General Sleep Disturbance Scale; ISI = Insomnia Severity Index; MDT = Multidisciplinary Team; MOS = Medical Outcomes Study Sleep Scale; PSQI = Pittsburgh Sleep Quality Index; RCT = Randomised Controlled Trial; SCI = Sleep Condition Indicator; WASO = Wake After Sleep Onset.

^aIndicates studies with statistically significant improvements in caregiver sleep outcomes.

Description of Interventions

Interventions trialled varied across studies and were broadly categorised into the following themes: carer sleep promoting interventions (n = 5), exercise interventions (n = 2), complementary alternative therapies (n = 2), technology-based support (n = 4) and carer psychological support (n = 5). Interventions had a mean duration of 20.7 weeks (Range 2–52 weeks).

Description of Outcome Measures

Measures of caregiver sleep outcomes were varied, with the majority of studies using more than one measure of sleep; six studies used actigraphy (Akkerman & Ostwald, 2004; Fowler et al., 2016; Friedman et al., 2012; Rowe et al., 2010; Sloane et al., 2015; Song et al., 2024), 11 studies used the Pittsburgh Sleep Quality Index (PSQI) (King et al., 2002; Kinnunen et al., 2018; Korn et al., 2009; Oken et al., 2010; Rose et al., 2009; Sanprakhon et al., 2023; Scheffer et al., 2025; Sloane et al., 2015; Song et al., 2024; Williams et al., 2019; Xu et al., 2022), four studies used sleep diaries (Friedman et al., 2012; Kinnunen et al., 2018; Rose et al., 2009; Rowe et al., 2010) and four studies used other measures (Friedman et al., 2012; Hirano et al., 2011; Kinnunen et al., 2018; Rose et al., 2009). No included studies utilised polysomnogrphy.

Risk of Bias

Risk of bias assessments are presented in Figure 2. Randomisation was the most well-reported domain, with four studies (22%) t assessed as low risk (Akkerman & Ostwald, 2004; Sloane et al., 2015; Song et al., 2024; Xu et al., 2022), and two studies (11%) were rated at high risk (Sanprakhon et al., 2023; Scheffer et al., 2025). 14 studies (78%) were assessed as having some concern in deviations from intended intervention domain c (Elliott et al., 2010; Friedman et al., 2012; Hirano et al., 2011; King et al., 2002; Kinnunen et al., 2018; Korn et al., 2009; Oken et al., 2010; Rapaport et al., 2024; Rose et al., 2009; Rowe et al., 2010; Sanprakhon et al., 2023; Scheffer et al., 2025; Sloane et al., 2015; Song et al., 2024), and one study (6%) (Fowler et al., 2016) was rated high risk. Missing outcome data was a notable source of bias, with six studies (33%) rated as of some concern (Elliott et al., 2010; Fowler et al., 2016; Kinnunen et al., 2018; Rowe et al., 2010; Sanprakhon et al., 2023; Scheffer et al., 2025) and three studies rated as high risk (Friedman et al., 2012; Hirano et al., 2011; King et al., 2002). Outcome measurement was a frequent concern, mostly due to lack of blinding or use of subjective outcomes. For this domain, only one study (6%) was low risk (Fowler et al., 2016), and four studies (22%) were rated as high risk (Akkerman & Ostwald, 2004; Elliott et al., 2010; Williams et al., 2019; Xu et al., 2022). Selection of reported results was a significant concern across the evidence base. Only three studies (17%) (Akkerman & Ostwald, 2004; Elliott et al., 2010; Fowler et al., 2016) were rated as low risk for selective reporting. Six studies (33%) (Friedman et al., 2012; Hirano et al., 2011; King et al., 2002; Korn et al., 2009; Oken et al., 2010; Rapaport et al., 2024) had some concerns, typically due to a lack of clear protocols and misalignment with pre specified plans. Notably, nine studies (50%) (Kinnunen et al., 2018; Rose et al., 2009; Rowe et al., 2010; Sanprakhon et al., 2023; Scheffer et al., 2025; Sloane et al., 2015; Song et al., 2024; Williams et al., 2019; Xu et al., 2022) were rated as high risk, representing the highest proportion of high-risk ratings across all domains. Overall, No studies achieved low risk of bias across all domains; Three studies (17%) had some concerns overall (Korn et al., 2009; Oken et al., 2010; Rapaport et al., 2024), while 15 studies (83%) were judged to have high overall risk of bias, primarily due to bias of selection of reported results (n = 9). A previous review of sleep interventions for carers identified similarly high levels of potential risk of bias (Pignatiello et al., 2022).

Figure 2.

Risk of bias analysis

Outcomes

Of the 18 included studies, seven (39%) demonstrated statistically significant improvements in at least one caregiver sleep outcome (Table 2). When grouped by intervention type, consistent patterns emerged: both exercise interventions (2/2, 100%) showed significant positive effects, while none of the technology-based interventions (0/4) or complementary therapy interventions (0/2) demonstrated statistically significant benefits for caregivers sleep. Sleep-promoting interventions showed mostly positive effects (3/5, 60%), while psychological support interventions showed mixed results (2/5, 40%). The remaining 11 studies did not yield statistically significant effects on sleep quality, however, numerous studies identified sleep outcome improvements which may be of clinical significance as detailed. For example, one study (Akkerman & Ostwald, 2004) did not undertake statistical analysis due to limited sample size but reported positive effects on sleep in the intervention group. The findings for each intervention category are described in detail below (Table 2).

Table 2.

Direction of Effects on Dementia Caregivers Sleep by Intervention Category

Intervention Type	Studies (n)	Studies With Statistically Significant Positive Effect	Studies With No Significant Effect	Direction of Evidence
Sleep promoting	5	3 (Friedman et al., 2012; Rapaport et al., 2024; Sloane et al., 2015)	2 (Kinnunen et al., 2018; Song et al., 2024)	Mixed
Exercise	2	2 (Hirano et al., 2011; King et al., 2002)	0	Positive
Complementary	2	0	2 (Korn et al., 2009; Rose et al., 2009)	No benefit demonstrated
Technology	4	0	4 (Fowler et al., 2016; Rowe et al., 2010; Scheffer et al., 2025; Williams et al., 2019)	No benefit demonstrated
Psychological	5	2 (Sanprakhon et al., 2023; Xu et al., 2022)	3 (Akkerman & Ostwald, 2004; Elliot et al., 2010; Oken et al., 2010)	Mixed
Total	18	7 (39%)	11 (61%)	Mixed

Sleep Promoting Interventions (n = 5)

All five sleep promoting intervention studies were dyadic interventions, which aimed to promote sleep in dementia caregivers, as well as the person living with dementia (Table 2). Three programs aimed to improve the sleep of the dyads via multi-component sleep promoting programs (Kinnunen et al., 2018; Rapaport et al., 2024; Song et al., 2024). A further two RCTs aimed to improve the sleep and/or circadian rhythms of dementia carers primarily via Bright Light Therapy (Friedman et al., 2012; Sloane et al., 2015).

Multi-Component Sleep Programs

Three studies delivered dyadic, multi-component sleep promoting interventions providing education around exercise, daylight exposure, psychological support, and dementia-related symptom management (including management of nocturnal agitation and sundowning) for carers.

One feasibility study provided caregivers with an intervention known as DREAMS START which consisted of education around daylight exposure, physical activity and management of symptoms of dementia, as well as undertaking CBT for insomnia (n = 62) (Kinnunen et al., 2018). Post-intervention, PSQI global scores showed no significant difference between groups (intervention: 9.37 ± 4.16 vs. control: 9.54 ± 4.49; adjusted treatment effect 1.03, 95% CI −1.05 to 3.11, p > 0.05), indicating the intervention did not significantly improve caregiver sleep quality. Following this feasibility work, a definitive phase 3 RCT of DREAMS START was conducted with 377 randomised dyads (Rapaport et al., 2024). Caregiver sleep was measured using the Sleep condition Indicator at 8 months (n = 259 caregivers), with significant improvements in sleep compared to controls (intervention: 17.60 ± 8.60 vs control: 15.73 ± 8.53; adjusted difference 1.84, 95% CI 0.32 to 3.35, p < 0.05). This represented an improvement from clinical insomnia at baseline to non-clinical levels post-intervention in the caregiver intervention group.

A similar dyadic manual-based intervention (Care2Sleep) delivered CBT for insomnia, light exposure, walking and behavioural problem-solving (n = 30 dyads) (Song et al., 2024). Caregivers sleep was measured via PSQI and actigraphy. Whilst improvements were noted at 3-month follow up, they were not significant, statistically or clinically (3.2% improvement in sleep efficiency p = 0.39; 12 minute decrease in total wake time p = 0.2; and non-significant improvements in PSQI measures).

Bright Light Therapy

Two sleep promoting interventions examined the use of dyadic light therapy as a means of potentially supporting circadian rhythms for both dyads and therefore improving carer sleep (Friedman et al., 2012; Sloane et al., 2015).

One study compared a 30 minute daily exposure to either bright white light (4,200 lux) versus dim red light (90 lux) for 2 weeks, with both groups also receiving sleep hygiene education (Friedman et al., 2012). Caregivers exposed to both BRIGHT light (4,200 lux) and DIM red light (90 lux) conditions showed significant improvements in actigraphy-measured wake after sleep onset (BRIGHT: −25 min, DIM: −16 min) and sleep efficiency (BRIGHT: +5%, DIM: +4%), with bright light showing statistically superior effects (p < 0.05, F (1,49) = 4.12) (Friedman et al., 2012). However, both groups also received sleep hygiene education, and the modest between-group differences suggest that sleep hygiene may have been the primary active component rather than light therapy alone.

Another light therapy intervention study evaluated a 6-week, in home blue-white light therapy using a crossover design (n = 17) (Sloane et al., 2015). This study demonstrated statistically significant benefits compared to red-yellow control light across multiple sleep measures: PSQI global scores (intervention: 3.7 vs control: 5.2, p = 0.013), MOS Sleep Problems scale (p = 0.011), MOS Sleep Adequacy (p = 0.046), and MOS Sleep Index (p = 0.012) (Sloane et al., 2015). However, caregivers’ baseline PSQI scores were already below the clinical threshold for poor sleep (mean 4.6, where >5 indicates poor sleep), limiting the clinical significance of these improvements and generalisability to caregivers with sleep disturbances.

Collectively, these findings suggest mixed evidence for sleep-promoting interventions in improving caregiver sleep. The large-scale DREAMS START trial (Rapaport et al., 2024) demonstrated clinically meaningful improvements, with caregivers transitioning from SCI-rated clinical insomnia to non-clinical sleep levels post-intervention. Light therapy interventions showed variable results: bright light produced statistically significant but modest improvements over dim light control when combined with sleep hygiene education (Friedman et al., 2012), while a smaller crossover trial (Sloane et al., 2015) demonstrated significant effects but in caregivers with already good baseline sleep (PSQI 4.6), limiting clinical applicability. Multi-component dyadic sleep education programs, particularly those incorporating CBT-I, exercise, and dementia management strategies, appear most promising for caregivers with clinically significant sleep disturbances.

Exercise Interventions (n = 2)

Two RCTs assessed the effects of moderate intensity exercise interventions on sleep in caregivers. One study subjectively measured sleep, however, the tool was not reported (Hirano et al., 2011), whilst the other study measured sleep quality using the PSQI (King et al., 2002). Both studies reported improved subjective sleep quality (Table 2).

A 12-month exercise intervention with 100 female caregivers demonstrated significant protection against declining sleep quality compared to an education control condition (F [6,74] = 2.9, p = 0.045) (King et al., 2002). While both groups experienced some decline in sleep quality over 12 months—typical in the caregiving trajectory—this decline was significantly attenuated in the physical activity group. Improvements in sleep quality were significantly associated with reductions in perceived stress (r = 0.33) and subjective carer burden (r = 0.33). No significant between-group differences were observed for sleep duration or sleep latency.

A 12-week moderate intensity exercise intervention study (n = 31) showed significant improvements in quality of sleep scores in the exercise group (change: −0.5, p = 0.04), while the control group demonstrated significant worsening (change: +0.7, p = 0.01) (Hirano et al., 2011). However, these results must be interpreted with caution given significant baseline differences between groups in sleep quality scores (exercise: 1.2 ± 0.9, control: 1.8 ± 0.8) and the use of an unvalidated sleep measurement tool.

Together, both studies demonstrated consistent statistically significant improvements in caregiver sleep following physical activity interventions, with exercise showing protective effects against declining sleep quality. While methodological limitations including baseline imbalances, small sample sizes, and use of non-validated measures in one study warrant caution, the consistent direction of effects across both trials suggests exercise interventions may offer a promising non-pharmacological approach to protecting caregiver sleep quality.

Complementary Alternative Therapies (n = 2)

Two RCTs described distinct complementary alternative therapy interventions, cranial electrical stimulation (CES) (Rose et al., 2009) and Polarity therapy (Korn et al., 2009). CES involved attaching two ear clips to participants (n = 38) and generating an imperceptible electrical current which aims to modulate neurotransmitters. Sleep quality was assessed via PSQI and general sleep disturbance scale (GSDS), 4 weeks post intervention. There were no statistically significant differences between the intervention group and the control group at the end of the trial (Rose et al., 2009).

Polarity therapy is an energy touch therapy which involves application of pressure on specific pressure points with the aim of unblocking and balancing energy flow (Korn et al., 2009). Sleep quality was assessed via PSQI with only global scores reported (n = 42). While not statistically significant (p = .16), polarity therapy demonstrated a 3.1-point global PSQI score reduction compared to 1.4 points in controls (Korn et al., 2009) which could be indicative of significant clinical improvement (Qin et al., 2024), although there is currently no consensus on whether a 3 or 4 point improvement is considered clinically relevant.

Neither complementary alternative therapies demonstrated statistically significant effects on caregiver sleep. While polarity therapy demonstrated trends toward improvement (1.7-point PSQI advantage over controls, p = .16) and cranial electrical stimulation showed marginal effects on daily disturbances (p = .09), neither intervention achieved statistical significance (Korn et al., 2009; Rose et al., 2009). Adequately powered trials are needed to determine whether these approaches offer clinically meaningful benefits.

Technology-Based Support (n = 4)

Four RCTs investigated the use of technology-based support systems and their impact on sleep quality (Fowler et al., 2016; Rowe et al., 2010; Scheffer et al., 2025; Williams et al., 2019). Two studies provided technology-mediated support to carers, with the other two utilising smart-home assistive technologies.

Two studies subjectively and objectively measured sleep using both questionnaires (sleep diary or insomnia severity index) and actigraphy (Fowler et al., 2016; Rowe et al., 2010), whilst the remaining two studies measured sleep using only the PSQI (Scheffer et al., 2025; Williams et al., 2019).

Technology-Mediated Carer Support

Two technology-mediated support interventions, aimed to provide an extra layer of carer support, delivered via technology (Fowler et al., 2016; Williams et al., 2019). FamTechCare is a telehealth video monitoring intervention whereby caregivers manually record and upload events and receive individualised feedback and support weekly from an expert team of reviewers (Williams et al., 2019). The intervention was provided for 3 months, with 83 caregivers enrolled. Subjective measures of sleep 3 months post intervention did not detect statistically significant changes (p = 0.839).

A similar study evaluated an internet based Virtual Healthcare Neighbourhood, whereby participants had access to online social support, educational materials and multi-disciplinary healthcare professionals (Fowler et al., 2016). A total of 28 dementia caregivers were enrolled into the study. While the intervention group showed minimal improvement in insomnia severity scores (15.3 to 14.3) compared to worsening in controls, there were no statistically significant improvements in either insomnia scores or actigraphy variables in the experimental group post-intervention (Fowler et al., 2016).

Smart-Home Assistive Technologies

Two technology-based support studies trialled in-home assistive technologies via smart home technology such as motion sensors, carer notifications and AI-powered recognition of unusual activity (Rowe et al., 2010; Scheffer et al., 2025). These technologies aimed to reduce carer vigilance and nighttime worry and thus optimise the opportunity to obtain sleep.

The People Power Caregiver system (n = 172) (Scheffer et al., 2025) demonstrated significant protection against PSQI-measured declining sleep efficiency through AI-powered selective alerting (p = .038, Cohen’s d = −0.76), however, these findings did not pass the false discovery rate (a statistical correction which controls for expected proportion of false positive results when multiple comparisons are made). Similarly, the Nighttime Monitoring System (n = 49) (Rowe et al., 2010) showed no improvements in either PSQI or actigraphy sleep measures, potentially due to alert fatigue from notifying caregivers of all nighttime activity rather than only concerning events.

Technology-based interventions showed limited effectiveness for improving caregiver sleep. While an AI-powered home monitoring system initially demonstrated protection against declining sleep efficiency (p = .038, Cohen’s d = −0.76), this finding did not survive false discovery rate correction for multiple comparisons (Scheffer et al., 2025). The remaining three interventions—two technology-mediated carer support platforms and one nighttime monitoring system—showed no significant effects on sleep quality or quantity.

Psychological Support (n = 5)

Five RCTs measured caregiver sleep as an outcome of an intervention aimed at improving caregivers psychological wellbeing (Akkerman & Ostwald, 2004; Elliott et al., 2010; Oken et al., 2010; Sanprakhon et al., 2023; Xu et al., 2022). Included studies evaluated diverse psychological approaches including Cognitive Behavioural Therapy (Akkerman & Ostwald, 2004), Mindfulness meditation (Oken et al., 2010), Integrative stress reduction (Sanprakhon et al., 2023) and dementia carer psycho-education (Elliott et al., 2010) and Behavioural Activation (BA) (Xu et al., 2022). One study measured sleep objectively via actigraphy (Akkerman & Ostwald, 2004) and the remaining four studies measured sleep via PSQI (Elliott et al., 2010; Oken et al., 2010; Sanprakhon et al., 2023; Xu et al., 2022).

Two psychological interventions demonstrated statistically significant improvement in caregiver sleep. An integrative stress reduction program (n = 54) delivered over 4 weeks showed significant PSQI improvements in the intervention group (baseline: 11.74 → week 8: 5.63, representing a clinically meaningful 6.1-point reduction) compared to controls (9.33 → 7.93), with large effect size (F [1, 51] = 24.45, p < .01; partial η² = 0.324) (Sanprakhon et al., 2023). Despite significant baseline differences between groups (p < .01), with the intervention group starting with worse sleep, the improvement crossed from clinical insomnia to borderline good sleep range.

BA is a psychological technique which may potentially improving sleep through indirect mechanisms associated with mood improvement and reduced rumination. An 8-week telephone-based BA program (n = 71) demonstrated statistically significant effects on Global Chinese-PQSI (C-PQSI) scores (F (1, 69) = 6.32, p = .014) and sleep efficiency F (1, 69) = 5.50, p = .022 (Xu et al., 2022). Additionally, sleep latency showed significant between-group differences (F (1, 69) = 8.02, p = .006). However, as with the stress reduction study, significant baseline differences existed between groups in sleep latency (p = .004) and sleep disturbance (p = .04), and the absence of raw scores for PSQI subdomains made clinical significance difficult to infer.

Three psychological interventions showed no significant effects on caregiver sleep. A 9-week, Cognitive behavioural therapy intervention study was delivered in a small group setting with sleep assessed via actigraphy in a sub-sample of participants (n = 5) (Akkerman & Ostwald, 2004). Preliminary results suggested a positive effect, with an average decrease in overnight wake time of 90 minutes at 10 weeks post-intervention; however, the limited sample size precluded statistical analysis. No statistically significant changes in PSQI measured sleep were noted following six sessions of mindfulness meditation in 31 carers (Oken et al., 2010). Similarly, a large multi-component, stress and burden reducing intervention (n = 495) delivered over 6 months measured sleep via a single question on a developed tool (REACH-II tool) and found no significant improvements in caregiver sleep (Elliott et al., 2010).

Taken together, psychological support interventions showed mixed evidence (2/5 studies with significant effects). Two studies demonstrated statistically significant improvements in caregiver sleep: a telephone-based behavioural activation program showed significant effects on global CPSQI scores (p = .014) and sleep efficiency (p = .022) (Xu et al., 2022), while an integrative stress reduction program produced clinically meaningful improvements, with caregivers’ PSQI scores improving 6.1 points from severe insomnia to borderline good sleep (p < .01, partial η² = 0.324) [25]. However, both studies had significant baseline differences between intervention and control groups, limiting interpretation despite statistical adjustment. A small CBT intervention (n = 5) showed promising preliminary results with 90-minute reductions in overnight wake time, but the sample size precluded statistical analysis (Akkerman & Ostwald, 2004). Mindfulness meditation (Oken et al., 2010) and multi-component psychoeducation (Elliott et al., 2010) showed no significant effects on caregiver sleep. These findings suggest that targeted psychological interventions, particularly stress reduction and behavioural activation approaches, may offer benefits for caregiver sleep, though larger methodologically rigorous trials with balanced baseline characteristics are needed.

Discussion

This systematic review synthesised evidence from 18 RCTs examining non-pharmacological interventions to improve sleep in dementia caregivers, representing the first comprehensive synthesis of evidence for this population. Seven studies (39%) demonstrated significant improvements in at least one measure of caregiver sleep with exercise-based interventions, sleep-promoting interventions and psychological support interventions showing most benefits. However, confidence in these findings is limited by substantial methodological concerns, with 83% of all studies deemed as having high risk of overall bias, including six of seven studies with statistically significant results. This prevalence of high risk of bias is in keeping with prior systematic reviews of sleep in dementia carers which identified 65% of studies as being of high risk of bias (Pignatiello et al., 2022). Moreover, of all seven studies with significant sleep improvements, only one measured sleep objectively, via actigraphy (Friedman et al., 2012). These findings both illuminate promising intervention approaches and underscore critical gaps in the evidence base that must be addressed to inform clinical practice. The findings for each intervention category are discussed below with attention to mechanism, clinical significance and implications for future research.

The most promising evidence emerged from sleep-promoting interventions. The large-scale DREAM-START RCT (n = 377) was the largest and most methodologically rigorous study included within the review. It demonstrated that a manualised, multi-component approach to improving carer sleep resulted in clinically meaningful improvements in sleep, with caregivers sleep improving from clinical insomnia to non-clinical levels, post intervention. Importantly, this study built on previous pilot work informing adequate sample sizing and allowing intervention adaption to ensure feasibility in a large-scale trial. Another multi-component program, Care2Sleep, had no significant effect on carer sleep (Song et al., 2024). The contrasting outcomes between these studies may reflect differences in statistical power—DREAMS START (n = 377) was adequately powered as a definitive phase 3 trial building on prior feasibility work, whereas Care2Sleep was a pilot study with insufficient power to detect modest effects (Song et al., 2024).

Light therapy studies results were more equivocal-whilst both studies showed statistically significant improvements, interpretation is complicated by methodological issues with one study illustrating statistically improvements in both control and intervention groups (attributed to sleep hygiene education received by both groups); and another study enrolled caregivers with good baseline sleep, potentially resulting in ceiling effects. Together, these limitations reduced ability to demonstrate efficacy for light therapy. Previous systematic reviews of effectiveness of light therapy in improving sleep among older adults have identified a lack of conclusive evidence and need for additional well-designed trials (Tan et al., 2022; Zhang et al., 2023). However, it is worth noting, light therapy (natural light exposure) was a key element of the successful DREAMS START study. Our findings suggest that rather than a single mode sleep promotion approach such as light therapy, multi-modal sleep-promoting programs combining a range of CBT-I, physical activity promotion and dementia management strategies show greater promise. This is in keeping with growing evidence for the success of multi-modal interventions in addressing the multi-factorial and individualised nature of caregiving and its complex impact (D'Cunha et al., 2025).

Both exercise interventions demonstrated that moderate intensity exercise provides protective effects against declining sleep quality for carers. These findings align with an abundance of studies in older adult populations, which have shown that physical activity improves sleep (Silva et al., 2022; Xie et al., 2021; Yang et al., 2012). However, both included studies had relatively small sample sizes, were deemed high risk of bias and one included study had significant baseline differences between groups (Hirano et al., 2011) and utilised an unvalidated sleep measurement tool. Despite these limitations, given the sleep-promoting effects and known positive impacts of exercise, these interventions warrant further investigation as a non-pharmacological means of improving carer sleep. While the exact mechanism by which exercise can lead to improvements in sleep in caregivers of a PLWD have not yet been investigated, it is possible that regular, moderate intensity exercise regulates hormones involved in the sleep-wake response, particularly melatonin (Buxton et al., 2003; Miyazaki et al., 2001). Future studies should assess the establishment of optimal exercise guidelines for caregivers to avoid overburdening a population that is already heavily leveraged (Brodaty & Donkin, 2009).

Within this review, psychological support interventions had variable effectiveness. Two psychological interventions demonstrated significant positive effects on carer sleep; Integrative stress reduction program (Sanprakhon et al., 2023) and telephone based behavioural activation (BA) program (Xu et al., 2022). Effectiveness of stress-reduction techniques on caregivers sleep quality aligns with previous literature demonstrating links between caregivers stress and sleep (Gao et al., 2019; Smyth et al., 2020), suggesting targeted reduction of stress may indirectly benefit sleep. Sleep and stress share a bidirectional physiological relationship whereby stress (and disrupted cortisol) disrupts sleep, and in turn, poor sleep can raise cortisol perpetuating the negative cycle. Despite statistical significance, as with prior intervention types, methodological concerns limit interpretation of stress-reduction effectiveness including significant baseline differences between control and intervention groups.

Similarly, whilst the BA program demonstrated significant effects on global sleep quality and sleep efficiency scores, methodological limitations makes it difficult to determine the clinical significance of the observed sleep improvements (Xu et al., 2022).

A small pilot study of group-based CBT-I showed promising preliminary actigraphy improvements, but the limited sample size (n = 5) precluded statistical analysis. There is a disappointing scarcity of CBT-I focused RCTs in dementia caregivers, given that it is an established first-line treatment for insomnia. This represents an important gap, especially given that CBT-I addresses many sleep-impacting factors prevalent in caregivers—such as hypervigilance, rumination, and worry—and has been shown to be acceptable and effective in treating sleep disorders in older adults (Huang et al., 2022; Smyth et al., 2023).

Conversely, mindfulness meditation and the large multi-component REACH-II psychoeducation program (n = 495) failed to improve sleep. Interestingly, mindfulness-based programs have been shown to improve sleep quality among informal carers in a recent systematic review (Safavi et al., 2025). These findings suggest that psychological interventions specifically targeting stress-reduction may be more effective than general psychoeducation or mindfulness approaches, though this would need to be confirmed by future adequately powered, well-designed RCTs.

No included technology-based interventions showed significant effects on caregivers sleep. Interventions included online carer support platforms and smart-home assistive technologies. The lack of effect on carer sleep outcomes may reflect the indirect nature of interventions, which aimed to reduce caregiver burden and vigilance, rather than specifically improve sleep. One nighttime monitoring technology appeared to worsen sleep for some participants through over-alerting of carers overnights, suggestive of poorly designed technology (Rowe et al., 2010). Similar issues have been identified in other research whereby nighttime monitoring system alerting was seen to cause more frequent wakening (Thomas et al., 2019). Whereas another AI-powered system using selective reporting showed initial promise for improving carer sleep, but findings failed false discovery rate correction for multiple comparisons (Scheffer et al., 2025). The contrasting findings suggest smarter technology design may hold potential; however, the current evidence base requires additional research. Despite the promise of technology-based interventions in improving caregivers experiences, there remains a paucity of well-designed, adequately powered RCTs evaluating the role of in-home assistive technology (Butler et al., 2023) in supporting carers in general and, in improving carer sleep. Future research is required to ensure technology solutions are appropriate, fit for purpose and engage consumer-led design.

Neither complementary therapies—polarity therapy (Korn et al., 2009) and cranial electrical stimulation (Rose et al., 2009)—demonstrated statistically significant effects on caregiver sleep. However, polarity therapy resulted in a three-point reduction in PSQI global scores suggesting potentially clinically significant results. Both studies had small sample sizes, underpowering them to detect moderate effects (n = 38–42). Additionally, there remains a lack of robust evidence supporting the sleep improving mechanism of either intervention. Given this limited evidence, future research should focus on scaling evidence-based approaches as a priority, until strong mechanistic rationale is established for these complementary therapies.

Strengths and Limitations

To the authors’ knowledge, this is the first comprehensive synthesis of RCT evidence examining non-pharmacological sleep interventions for dementia caregivers. By limiting studies to RCTs, this review focused on the highest quality intervention evidence, although in turn, this excluded other, potentially informative, non-randomised studies which may provide further insights. The systematic approach ensures methodological rigour, however, several limitations warrant consideration.

In keeping with prior reviews of sleep promoting interventions across all caregiver types, we found that studies in dementia caregiver groups were often highly heterogeneous, with methodological shortcomings and limited evidence to support their efficacy (Cooper et al., 2022; Fernández-Puerta et al., 2022; Pignatiello et al., 2022). Most critically, 83% of included studies were deemed to have an overall high risk of bias. These methodological limitations impact confidence in generalisability of the findings and highlight the known deficiencies in existing evidence base across dementia research. Sample sizes were often small, limiting statistical power and increasing likelihood of potential both false negative and false positive findings. While it is notoriously difficult to recruit and retain dementia caregiver populations for research, due to the competing demands of caregiving (Hirt et al., 2024), larger sample sizes are essential for appropriately powered trials to generate definitive evidence. Recruitment methods were also noted to be sub-optimal in some studies with baseline characteristics shown to be either significantly different between groups or not indicative of populations with poor sleep, again impacting the generalisability of findings to caregivers with clinically significant sleep disturbances.

Beyond sample size and baseline characteristic issues, substantial heterogeneity in intervention types, duration, delivery mode and sleep outcome measures, precluded meta-analysis. This level of heterogeneity and the associated difficulty in undertaking meaningful and robust meta-analysis has been identified in other reviews of sleep promoting interventions (Cooper et al., 2022). Even among studies using PSQI, many failed to report subscale scores, preventing detailed analysis of which domains improved. The use of narrative synthesis was essential to avoid the methodological error of inappropriately pooling fundamentally different interventions (Campbell et al., 2020). This approach allowed comprehensive comparison of diverse interventions while avoiding false findings from forcing statistical pooling of widely heterogeneous studies.

Sleep was often a secondary outcome rather than a primary outcome, potentially resulting in less rigorous sleep assessment and targeting. Future studies should prioritise sleep as a primary outcome, ensure validated subjective and objective sleep measures, to allow for meaningful cross-study comparisons and assessment of intervention effects across multiple sleep domains. No included studies utilised polysomnography, despite this being the gold standard objective measure of sleep. This may reflect the practical constraints of caregiver research whereby sleep must be measured in the home environment to accommodate overnight caregiving responsibilities, limiting feasibility of laboratory-based PSG measurement.

Finally, the caregiver population itself was relatively homogenous; predominately female, limited ethnic diversity and primarily from high-income countries, resulting in uncertain generalisability to male caregivers, culturally and linguistically diverse carers or low-resource settings.

Conclusion

Overall, RCTs investigating the effects of non-pharmacological interventions on sleep quality in caregivers of a PLWD are limited and generally have a high risk of bias, highlighting the need for future work to be well designed, adequately powered RCTs. Evidence from our included RCTs suggests that certain non-pharmacological interventions, particularly multi-component sleep-promoting programs, stress reduction interventions and exercise interventions, show promise for improving dementia caregivers sleep. It is worth noting that insufficient evidence in other intervention types (particularly technology and complementary therapies) does not determine that intervention to be of no value, rather, it means that the evidence base is sparse and therefore meaningful conclusions cannot be drawn at this time.

Improving caregivers sleep has wide-ranging implications beyond individual wellbeing. Poor carer sleep is associated with psychological distress, higher levels of carer burden, decreased carer physical health, increased risk of institutionalisation and reduced quality of care. Establishing a body of evidence to inform effective, scalable sleep interventions can have profound positive impacts in the carer, care recipient and the broader health system. However, this requires substantial investment in high-quality research to build a robust evidence base to inform best practice.

Supplemental Material

Supplemental Material—Non-pharmacological Sleep Interventions for Dementia Caregivers; a Systematic Review of Randomised Controlled Trials

Supplemental Material for Non-pharmacological Sleep Interventions for Dementia Caregivers; a Systematic Review of Randomised Controlled Trials by Aisling Smyth, Krishna Lambert, Mark Jenkins, Adugnaw Zeleke Alem, Misganaw Gebrie Worku, Sujatha Shanmugasundaram in Journal of Applied Gerontology.

Supplemental Material

Supplemental Material—Non-pharmacological Sleep Interventions for Dementia Caregivers; a Systematic Review of Randomised Controlled Trials

Footnotes

ORCID iD

Aisling Smyth

Ethical Considerations

As this systematic review utilised publicly available data, no ethical approval was required.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by an RM Gibson grant from the Australian Association of Gerontology, granted to AS. All work was completed independently by authors without input from grant providers.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on request.*

Supplemental Material

Supplemental material for this article is available online.

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